首页> 外文会议>Advances in Neural Networks - ISNN 2007 pt.2; Lecture Notes in Computer Science; 4492 >An Improve to Human Computer Interaction, Recovering Data from Databases Through Spoken Natural Language
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An Improve to Human Computer Interaction, Recovering Data from Databases Through Spoken Natural Language

机译:人机交互的一种改进,通过自然语言从数据库中恢复数据

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The fastest and most straightforward way of communication for mankind is the voice. Therefore, the best way to interact with computers should be the voice too. That is why at the moment men are searching new ways to interact with computers. This interaction is improved if the words spoken by the speaker are organized in Natural Language. In this article, it is proposed a model to recover information from databases through queries in Spanish Natural Language using the voice as the way of communication. This model incorporates a Hybrid Intelligent System based on Genetic Algorithms and a Kohonen Self-Organizing Map (SOM) to recognize the present phonemes in a word through time. This approach allows us to remake up a word with speaker independence. Furthermore, it is proposed the use of a compiler with type 2 grammar according to the Chomsky Hierarchy to support the syntactic and semantic structure in Spanish language. Our experiments suggest that the Spoken Natural Language improves notably the Human-Computer interaction when compared with traditional input methods such as: mouse or keybord.
机译:语音是人类最快最直接的交流方式。因此,与计算机交互的最佳方式也应该是声音。这就是为什么现在人们正在寻找与计算机交互的新方法的原因。如果说话者说的话是用自然语言组织的,则可以改善这种互动。在本文中,提出了一种模型,该模型可以通过使用语音作为通信方式的西班牙语自然语言中的查询从数据库中恢复信息。该模型结合了基于遗传算法和Kohonen自组织映射(SOM)的混合智能系统,可以识别整个单词中的当前音素。这种方法使我们能够重塑说话者的独立性。此外,建议根据乔姆斯基体系使用具有2型语法的编译器来支持西班牙语的句法和语义结构。我们的实验表明,与传统输入法(例如鼠标或键盘)相比,口语自然语言显着改善了人机交互。

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